Barrier Lyapunov Functions for the control of output-constrained nonlinear systems
Automatica (Journal of IFAC)
Adaptive iterative learning control for robot manipulators
Automatica (Journal of IFAC)
Iterative learning control design based on composite energy function with input saturation
Automatica (Journal of IFAC)
| Hi-index | 22.14 |
In this work, by proposing a Barrier Composite Energy Function (BCEF) method with a novel Barrier Lyapunov Function (BLF), we present a new iterative learning control (ILC) scheme for a class of single-input single-output (SISO) high order nonlinear systems to deal with output-constrained problems under alignment condition with both parametric and nonparametric system uncertainties. Nonparametric uncertainties such as norm-bounded nonlinear uncertainties satisfying local Lipschitz condition can be effectively handled. Backstepping design with the newly proposed BLF is incorporated in analysis to ensure output constraint not violated. Through rigorous analysis, we show that under this new ILC scheme, uniform convergence of state tracking error is guaranteed. In the end, an illustrative example is presented to demonstrate the efficacy of the proposed ILC scheme.